Enhancing Tit-for-Tat Strategy to Cope with Free-Riding in Unreliable P2P Networks

2008 ◽  
Author(s):  
Dongsheng Peng ◽  
Weidong Liu ◽  
Chuang Lin ◽  
Zhen Chen ◽  
Xuehai Peng
Keyword(s):  
Free Riding ◽  
P2p Networks ◽  
Tit For Tat

scholarly journals “Q-Feed”—An Effective Solution for the Free-Riding Problem in Unstructured P2P Networks

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Sabu M. Thampi ◽  
Chandra Sekaran K
Keyword(s):  
Control Mechanism ◽  
Free Riding ◽  
Effective Solution ◽  
P2p Networks ◽  
Q Learning ◽  
Free Riders ◽  
Replication Scheme ◽  
Simulation Results ◽  
Unstructured P2p ◽  
Different Levels

This paper presents a solution for reducing the ill effects of free-riders in decentralised unstructured P2P networks. An autonomous replication scheme is proposed to improve the availability and enhance system performance. Q-learning is widely employed in different situations to improve the accuracy in decision making by each peer. Based on the performance of neighbours of a peer, every neighbour is awarded different levels of ranks. At the same time a low-performing node is allowed to improve its rank in different ways. Simulation results show that Q-learning-based free riding control mechanism effectively limits the services received by free-riders and also encourages the low-performing neighbours to improve their position. The popular files are autonomously replicated to nodes possessing required parameters. Due to this improvement of quantity of popular files, free riders are given opportunity to lift their position for active participation in the network for sharing files. Q-feed effectively manages queries from free riders and reduces network traffic significantly.

scholarly journals A Peer-to-Peer Reputation Evaluation System

10.29007/hm9m ◽  
2019 ◽  
Author(s):  
Ming-Chang Huang
Keyword(s):  
Fuzzy Logic ◽  
Evaluation System ◽  
Free Riding ◽  
Peer To Peer ◽  
Service Differentiation ◽  
Reputation System ◽  
P2p Networks ◽  
Input Information ◽  
Fuzzy Logic Method ◽  
Logic Method

Lack of incentives makes most P2P users unwilling to cooperate and lead to free-riding behavior. One way to encourage cooperation is through service differentiation based on each peer’s contributions. This paper presents FuzRep, a reputation system for P2P networks. FuzRep uses fuzzy logic method which uses requester’s reputation and provider’s inbound bandwidth as input information to create incentives for sharing and to avoid overloading problems for primary file providers. Reputation sharing in FuzRep is implemented by interest-based selective polling, which can significantly decrease overheads for reputation communication.

Sign in / Sign up

Export Citation Format

Share Document